The Solving Cholera Infection Model using Runge-Kutta Fourth Order Method

Abstract

In this study, Runge-Kutta fourth order method (RK4) is used to simulate the spread of cholera in a population. This cholera infection model were solved by using RK4 and the results obtained were compared between two different step sizes: 0.1 and 0.01. The results showed that the choice of step size has a significant impact on the accuracy and computation time of the model. A smaller step size increases the accuracy of the solution but prolongs the computation time, while a larger step size decreases the accuracy but reduces the computation time. We found that a balance needs to be struck between the need for accuracy and the need for computational efficiency when choosing the step size for RK4 method. Our model also showed that as the time progress, the susceptible individuals decrease, vaccinated individuals increase, infectious individuals decrease, concentration of toxigenic vibrio cholerae decrease, and recovery individuals increase. Our study highlights the importance of considering the specific research goals and computational resources when solving a cholera infection model using RK4. Additionally, the model's assumptions and simplifications, data availability, and ethical implications should be taken into account when interpreting the results.